{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Alessandro Parisi \n",
      "last updated: 2019-04-16 \n",
      "\n",
      "CPython 3.5.4\n",
      "IPython 6.1.0\n",
      "\n",
      "numpy 1.15.2\n",
      "pandas 0.23.4\n",
      "matplotlib 2.2.2\n",
      "sklearn 0.20.0\n",
      "seaborn 0.8.0\n"
     ]
    }
   ],
   "source": [
    "%load_ext watermark\n",
    "%watermark -a \"Alessandro Parisi\" -u -d -v -p numpy,pandas,matplotlib,sklearn,seaborn\n",
    "# to install watermark launch 'pip install watermark' at command line\n",
    "import warnings \n",
    "warnings.simplefilter('ignore')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "from matplotlib import pyplot as plt\n",
    "%matplotlib inline\n",
    "\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn import metrics\n",
    "\n",
    "from sklearn.neighbors import KNeighborsClassifier\n",
    "from sklearn import svm\n",
    "from sklearn.neural_network import MLPClassifier"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "pwd_data = pd.read_csv(\"../datasets/DSL-StrongPasswordData.csv\", header = 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x93e63b75c0>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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FihXMmDGDvXv3MnbsWDw8PJg1axbPPvsst99+O/fccw/e3t7s2LEDb29vZ7wMohMx2cZP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Sawozvndt7g3M4b9J7c/P4H+C+kMnjuF/hlIPwxEYwtwbcb74a+S//N/QlueRBZzni+3BPDwZhM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\nAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Average Keystroke Latency per Subject\n",
    "\n",
    "DD = [dd for dd in pwd_data.columns if dd.startswith('DD')]\n",
    "plot = pwd_data[DD]\n",
    "plot['subject'] = pwd_data['subject'].values\n",
    "plot = plot.groupby('subject').mean()\n",
    "\n",
    "plot.iloc[:6].T.plot(figsize=(8, 6), title='Average Keystroke Latency per Subject')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "data_train, data_test = train_test_split(pwd_data, test_size = 0.2, random_state=0)\n",
    "\n",
    "X_train = data_train[pwd_data.columns[2:]]\n",
    "y_train = data_train['subject']\n",
    "\n",
    "X_test = data_test[pwd_data.columns[2:]]\n",
    "y_test = data_test['subject']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "K-Nearest Neighbor Classifier Accuracy: 0.3730392156862745\n"
     ]
    }
   ],
   "source": [
    "knc = KNeighborsClassifier()\n",
    "knc.fit(X_train, y_train)\n",
    "\n",
    "y_pred = knc.predict(X_test)\n",
    "\n",
    "knc_accuracy = metrics.accuracy_score(y_test, y_pred)\n",
    "print('K-Nearest Neighbor Classifier Accuracy:', knc_accuracy)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Support Vector Linear Classifier Accuracy: 0.7629901960784313\n"
     ]
    }
   ],
   "source": [
    "svc = svm.SVC(kernel='linear') \n",
    "svc.fit(X_train, y_train)\n",
    "\n",
    "y_pred = svc.predict(X_test)\n",
    "\n",
    "svc_accuracy = metrics.accuracy_score(y_test, y_pred)\n",
    "print('Support Vector Linear Classifier Accuracy:', svc_accuracy)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Multi Layer Perceptron Classifier Accuracy: 0.9034313725490196\n"
     ]
    }
   ],
   "source": [
    "mlpc = MLPClassifier()\n",
    "mlpc.fit(X_train,y_train)\n",
    "\n",
    "y_pred = mlpc.predict(X_test)\n",
    "\n",
    "mlpc_accuracy = metrics.accuracy_score(y_test, y_pred)\n",
    "print('Multi Layer Perceptron Classifier Accuracy:', mlpc_accuracy)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0,0.5,'True')"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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OmTWrvojnnx9PRONStX6I1WriMbNJIwK2DU9p+8hD0mxJ10q6V9JaScd4oXozGygFrqny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\nAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.metrics import confusion_matrix\n",
    "\n",
    "labels = list(pwd_data['subject'].unique())\n",
    "cm = confusion_matrix(y_test, y_pred, labels) \n",
    "\n",
    "figure = plt.figure()\n",
    "axes = figure.add_subplot(111)\n",
    "figure.colorbar(axes.matshow(cm))\n",
    "axes.set_xticklabels([''] + labels)\n",
    "axes.set_yticklabels([''] + labels)\n",
    "plt.xlabel('Predicted')\n",
    "plt.ylabel('True')"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Py35",
   "language": "python",
   "name": "py35"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.5.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
